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This paper describes the development of a knowledge management framework for the “new product introduction process” of Motorola. Motorola operates in a very dynamic business with short product cycles, and has a clear need, therefore, to leverage the knowledge available worldwide. After developing a theoretical framework that reflected Motorola’s business processes, a large‐scale survey among workers at different locations in the world was conducted. The survey results were used for the design of a knowledge management framework, which supports sharing of various types of knowledge on different business levels.

Managers are increasingly looking to adopt the Internet of Things (IoT) to include the vast amount of big data generated in their decision-making processes. The use of IoT might yield many benefits for organizations engaged in civil infrastructure management, but these benefits might be difficult to realize as organizations are not equipped to handle and interpret this data. The purpose of this paper is to understand how IoT adoption affects decision-making processes.

In this paper the changes in the business processes for managing civil infrastructure assets brought about by IoT adoption are analyzed by investigating two case studies within the water management domain. Propositions for effective IoT adoption in decision-making processes are derived.

The results show that decision processes in civil infrastructure asset management have been transformed to deal with the real-time nature of the data. The authors found the need to make organizational and business process changes, development of new capabilities, data provenance and governance and the need for standardization. IoT can have a transformative effect on business processes.

Because of the chosen research approach, the research results may lack generalizability. Therefore, researchers are encouraged to test the propositions further.

The paper shows that data provenance is necessary to be able to understand the value and the quality of the data often generated by various organizations. Managers need to adapt new capabilities to be able to interpret the data.

This paper fulfills an identified need to understand how IoT adoption affects decision-making processes in asset management in order to be able to achieve expected benefits and mitigate risk.

Although scholars have provided sufficient empirical evidence on the effect of peer knowledge hiding on new product development (NPD) project team outcomes, little attention has been given to the relationship between project manager knowledge hiding and individual outcomes. Drawing on the job resources-demands model and a dyadic stressor perspective, this study aims to explore the effect of project manager knowledge hiding on subordinates’ turnover intentions as well as the mediating roles of challenge- and hindrance-related stress.

This study conducted a multiple-source survey of NPD project managers and their subordinates in China. Hypotheses were tested by using data collected from 171 manager–subordinate dyads in NPD projects.

The findings revealed that project manager knowledge hiding was positively associated with subordinates’ turnover intentions, challenge-related stress and hindrance-related stress. Project manager knowledge hiding imposed a positive indirect effect on turnover intentions through hindrance-related stress, whereas the mediating effect of challenge-related stress was not significant.

To the best of the authors’ knowledge, this study is one of the first to investigate the individual outcomes of top-down knowledge hiding as well as the mediating roles of challenge- and hindrance-related stress in the context of NPD projects.

Crowdsourcing food delivery represents great potential for future development and expansion of the restaurant business. Accordingly, job performance and retention of delivery workers are critical for success. Therefore, this paper aims to investigate how to enhance crowdsourced delivery workers’ job performance and intent to continue working by applying the sociotechnical systems theory.

The data analysis was conducted using responses obtained from crowdsourced food delivery workers. A structural equation model was developed to verify the hypothesized relationships. To test the proposed moderating roles of a three-dimensional concept of social capital within the research model, multi-group analyses were implemented.

This study confirmed the significant relationships between crowdsourcing risks related to workers’ low job commitment and technical systems, attributing to reduced job performance and intent to continue working. Results documented that social systems including networks, trust and shared vision mitigated the negative impact of the perceived difficulty and complexity of technical systems and job performance.

Although technology has contributed significantly to the effectiveness of online food delivery, the literature has mainly focused on its benefits and has ignored the critical aspects derived from a virtual and technology-based workplace. This gap was addressed by verifying the important roles of social factors (networks, trust and shared visions) in reducing the negative impacts of technology-driven risks (perceived difficulty of task requirements and technology complexity) within the crowdsourcing food delivery context.

While climate change mitigation policies are indispensable for addressing global environmental crises, the chapter prompts that their implementation should account for the intricate tapestry of territorial identities. The solution lies in a balanced approach that harmonizes emission reduction targets with the preservation of cultural heritage and local customs. The chapter concludes by warning against top-down imposition of policies, as this could jeopardize community autonomy and engender mistrust. Given the delicate balance between climate concerns and cultural preservation, a path forward emerges, that upholds the integrity of desirable territorial development.

This chapter reviews Internet of Things (IoT) as a concept with bibliometric analysis using data selected from the Scopus database. The cited references included two clusters. Also, co-occurrence keyword analysis found four groups. The first cluster shows IoT adoption in agriculture, manufacturing, logistics, and supply chain management. The second cluster includes behavioral models of IoT technology acceptance. The third cluster refers to the adoption of IoT and automation technology in intelligent buildings, smart homes, smart cities, and health care. Finally, the fourth cluster contains information management.

This study aims to explore whether frontline employees' service recovery performance as well as customers' recovery satisfaction (RS) act as mediating mechanisms that simultaneously transmit the positive influence of an integrated service recovery system (SRS) on customers' service loyalty (SL).

A total of 134 useable retail banking branch cases (including responses from 134 branch heads, 439 frontline employees and 941 customers) were used to test our model using the partial least squares structural equation modeling (PLS-SEM) approach.

Service recovery system, measured as a higher-order multidimensional construct, has a strong and positive influence on customers' SL. Besides, service recovery performance partially mediates, along with RS, the relationship between SRS and SL. Finally, customers' recovery satisfaction has the strongest influence on service loyalty.

This study strongly suggests that practitioners not only focus on implementing an effective SRS but also on leveraging service recovery performance and RS to build sustained customers' loyalty. Practitioners must provide more attention to training their frontline employees, reward and recognize employees and continually evaluate their employees' recovery efforts.

The role of frontline employees' service recovery performance and customers' RS as mediating mechanisms in transmitting the positive effect of SRS on customers' SL is investigated using the combined perspectives of social-technical system theory and interdependence theory.

The purpose of this paper is to highlight the ontological implications of combining network and system ontology to conceptualize industrial networks as the empirical manifestations of complex adaptive economic systems.

This paper contributes with a systematic discussion on how network and system ontology can be combined to produce better understandings of business networks. It also provides a review of the state-of-the art research literature on the topic as a starting point for the discussion.

Findings indicate that networks may be enclosed in each other constituting sub- and supra-networks comprising increasing complexity. In these cases, sub-networks that are black-boxed can be seen as entities in themselves producing inputs and outputs to the supra-network. Networks, once they become black-boxed, can assume the functions of generative mechanisms within a wider supra-network.

This research is conceptual in nature and needs to be complemented with empirical research. In addition, the literature review used one database complemented with papers from the IMP journal. A wider search could reveal additional research that can be of relevance for the development of the field.

This paper addresses the ontological and methodological issues arising from a mixed system and network ontology. These issues are commonly ignored or dealt with indirectly in extant literature. For any accumulation of knowledge in the field to be possible, the explication of a mixed ontology is important as it have conceptual and methodological consequences. Adopting such a mixed ontological position provides an ontology in line with empirical research of business practice.

A recent study reported that businesses with good knowledge management (KM) clearly outperformed those without it. The authors of the study – Kluger et al. – were able to grasp the intangible benefits of sound knowledge management, relate them to business results and conclude that KM indeed stimulates the performance of an organization.

Management and risk techniques within industries have been studied from various disciplines in nondefense-affiliated industries. Given the assumption that these techniques, strategies and mitigations used in one industry apply to other similar industries, this paper examines the defense industry for risk assessment. We characterize interactions for onward application to risk identification in the defense industry.

This research employs a systems theory approach to the characterization of industry interactions, using three dimensions including environment, boundaries and relationships. It develops a framework for identifying relationship types within system-of-systems (SoS) environments by analyzing the features of interactions that occur in such environments.

The study’s findings show that different systems environments within the defense industry SoS exhibit different interaction characteristics and hence display different relationship patterns, which can indicate potential vulnerabilities.

By employing interaction as a means for evaluating potential risks, this research emphasizes the role played by relationship factors in reducing perceived risks and simultaneously increasing trust.

This paper intends to develop an initial snapshot of the relationship status of the Swedish defense industry in light of the global consolidation in this industry, which is a relevant contextual contribution.